Publisher
Springer Nature Singapore
Reference37 articles.
1. Zhang, K., Liang, J., Zhao, X., et al.: A Collaborative Filtering Recommendation Algorithm Based on Information of Community Experts (2018)
2. Aditya, P.H., Budi, I., Munajat, Q.: A comparative analysis of memory-based and model-based collaborative filtering on the implementation of recommender system for E-commerce in Indonesia: a case study PT X. In: 2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS). IEEE (2017)
3. Kamishima, T., et al.: Model-based approaches for independence-enhanced recommendation. In: IEEE International Conference on Data Mining Workshops IEEE (2017)
4. Pavlov, D.Y., Pennock, D.M.: A maximum entropy approach to collaborative filtering in dynamic, sparse, high-dimensional domains. In: International Conference on Neural Information Processing Systems. MIT Press (2002)
5. Liu, K., Wei, L., Chen, X.: A new preference-based model to solve the cold start problem in a recommender system. In: Proceedings of the 2nd International Conference on Electromechanical Control Technology and Transportation (ICECTT 2017) (2017)